Cowork Chrome Extension Automates Personal Data Removal from Data Brokers

Cowork (link) is a Chrome extension that uses your Gmail account to automate data removal from major data brokers. A Reddit user on r/ClaudeAI shared their experience: they connected the extension to Gmail, filled all opt-out forms, wrote the required emails, and verified each removal — all without manual intervention. Within hours, they started receiving removal confirmation emails from multiple providers.
Unlike paid services like Incogni that require subscriptions and have upsells, Cowork is free and operates entirely client-side. The process is straightforward:
- Install the Cowork Chrome extension.
- Connect your Gmail account.
- Let it automatically fill forms, compose emails, and verify removals.
The user reported that the process completed before the weekend, and by the start of the next week they had received multiple removal notifications. This is a practical, no-cost alternative to subscription-based data removal services.
📖 Read the full source: r/ClaudeAI
👀 See Also

The Companies Cutting Headcount for AI Will Lose to the Ones Who Didn't
AI headcount cuts trade long-term institutional knowledge for short-term savings. Retaining teams and using AI to amplify their capability is the winning strategy.

the-knowledge-guy: Turn Your Bookshelf Into a Tutor With Claude Code Skills
A Claude Code skill set that ingests your PDF/EPUB books locally and lets you ask questions, get taught topic-by-topic, or pull cheatsheets — all with citations across your library.

Knowledge Raven: A Model-Agnostic Knowledge Base Platform Built with Claude Code
Knowledge Raven is a knowledge base platform that lets any MCP-compatible LLM search and cite company documents. The entire platform was built with Claude Code by a solo founder, featuring Python/FastAPI backend, MCP tool layer, and agentic RAG pipeline.
Spine Swarm: Multi-Agent AI System on Visual Canvas for Non-Coding Projects
Spine Swarm is a multi-agent system that works on an infinite visual canvas to complete complex non-coding projects like competitive analysis, financial modeling, SEO audits, pitch decks, and interactive prototypes. The system uses blocks as abstractions on top of AI models that can be connected to pass context between different model types.